Cardiotoxicity in Children With Acute Ieukemia Treated by Anthracycline; Detected by Cardiac Troponins and Echcocardiography by Yaran Abbas Abdulqader, Mouroge Hashim Al-Ani, Nadine Abdulrazzak Mahmood

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Small target detection in UAV view based on improved YOLOv8 algorithm by Xiaoli Zhang, Guocai Zuo

“…Abstract The main challenges faced when detecting targets captured by UAVs include small target image size, dense target distribution, and uneven category distribution.In addition, the hardware limitations of UAVs impose constraints on the size and complexity of the model, which may lead to poor detection accuracy of the model. …”
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Detecting Malicious URLs Using Classification Algorithms in Machine Learning and Deep Learning by Sira Astour, Ahmad Hasan

“…Traditional methods of detecting malicious URLs are often insufficient and require advanced technologies. …”
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A Real Time Cardiomyopathy Detection Tool Using Ml Ensemble Models by Salvador de Haro, Esteban Becerra, Pilar González-Férez, José M. García, Gregorio Bernabé

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Transfer Learning Model for Crack Detection in Side SlopesBased on Crack-Net by Na Li, Yilong Zhang, Qing Zhang, Shaoguang Zhu

“…Accurate detection of slope cracks plays a crucial role in early landslide disaster warning; however, traditional approaches often struggle to identify fine and irregular cracks. …”
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Reinforced Cost-Sensitive Graph Network for Detecting Fraud Leaders in Telecom Fraud by Peiwen Gao, Zhihua Li, Dibin Zhou, Liang Zhang

“…These leaders orchestrate scams through intermediaries rather than directly engaging in fraudulent activities. Additionally, the significantly smaller number of fraudulent users than benign users further complicates the detection process. …”
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Mode Selection Model for Rail Crack Detection Based on Ultrasonic Guided Waves by Bo Xing, Zujun Yu, Xining Xu, Liqiang Zhu, Hongmei Shi

“…The model can effectively select guided wave modes suitable for detecting arbitrary cracks on rails, which provides a theoretical solution for rail crack detection.…”
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Malware Detection in Forensic Memory Dumps: The Use of Deep Meta-Learning Models by Yalçın Özkan

“…The predictive model was found to have an accuracy metric of 98.25%. In addition to this finding, a meta-learning model consisting of five different models with the same hyperparameters was created. …”
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Detection of Weak Radar Return Signals Based on Pseudo-Time Domain Algorithm by Kaili Wang, Kai Yuan, Bo Bai, Rongxin Tang

“…Radar systems, particularly those on small platforms like drones and satellites, often face this challenge due to limited power, resulting in low transmit power and weak signals. Additionally, ambient noises in the detection environment can further obscure the echo signal, leading to low SNR. …”
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G-RCenterNet: Reinforced CenterNet for Robotic Arm Grasp Detection by Jimeng Bai, Guohua Cao

“…In industrial applications, robotic arm grasp detection tasks frequently suffer from inadequate accuracy and success rates, which result in reduced operational efficiency. …”
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Overcoming data scarcity in life-threatening arrhythmia detection through transfer learning by Giuliana Monachino, Beatrice Zanchi, Michael Wand, Giulio Conte, Athina Tzovara, Francesca Dalia Faraci

“…Results Our model achieves a sensitivity of 92.68% and a specificity of 99.48%, with a granularity of 1.28 seconds, in detecting LTAs. Additionally, a confidence estimation procedure is introduced to enable emergency service pre-alerts in case of low-confidence detections. …”
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Cluster Embedding Joint-Probability-Discrepancy Transfer for Cross-Subject Seizure Detection by Xiaonan Cui, Jiuwen Cao, Xiaoping Lai, Tiejia Jiang, Feng Gao

“…Transfer learning (TL) has been applied in seizure detection to deal with differences between different subjects or tasks. …”
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Cross-Scale Hypergraph Neural Networks with Inter–Intra Constraints for Mitosis Detection by Jincheng Li, Danyang Dong, Yihui Zhan, Guanren Zhu, Hengshuo Zhang, Xing Xie, Lingling Yang

“…Our model introduces a block-based feature extraction mechanism to efficiently capture deep representations. Additionally, we leverage hypergraph convolutional networks to process both intracellular and intercellular information, leading to more precise diagnostic outcomes. …”
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Few-Shot Graph Anomaly Detection via Dual-Level Knowledge Distillation by Xuan Li, Dejie Cheng, Luheng Zhang, Chengfang Zhang, Ziliang Feng

“…Graph anomaly detection is crucial in many high-impact applications across diverse fields. …”
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Enhancing Propaganda Detection in Arabic News Context Through Multi-Task Learning by Lubna Al-Henaki, Hend Al-Khalifa, Abdulmalik Al-Salman

“…The current study addresses this gap by introducing the first multi-task learning (MTL) models for Arabic propaganda detection, integrating sentiment analysis and emotion detection as auxiliary tasks. …”
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HTC-HAD: A Hybrid Transformer-CNN Approach for Hyperspectral Anomaly Detection by Minghua Zhao, Wen Zheng, Jing Hu

“…Hyperspectral anomaly detection (HAD) identifies anomalies by analyzing differences between anomalies and background pixels without prior information, presenting a significant challenge. …”
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The Main Arboviruses and Virus Detection Methods in Vectors: Current Approaches and Future Perspectives by Amanda Montezano Cintra, Nathália Mayumi Noda-Nicolau, Milena Leite de Oliveira Soman, Pedro Henrique de Andrade Affonso, Guilherme Targino Valente, Rejane Maria Tommasini Grotto

“…These features are essential for guiding the development and implementation of specific and sensitive detection strategies. In addition, this work provides a comparative analysis of diverse laboratory methodologies for viral detection in vectors. …”
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Improved ASCVD Screening in Diabetes: a Focus on Scoring Models and Detection Techniques by Zanfirescu Răzvan-Liviu, Anghel Larisa, Tudurachi Bogdan-Sorin, Clement Alexandra-Mihaela, Zăvoi Alexandra, Benchea Laura-Cătălina, Ciocoiu Manuela, Sascău Radu Andy, Stătescu Cristian, Radu Rodica

“…Emerging tools, such as non-invasive imaging techniques (e.g., coronary artery calcium scoring, CCTA) and biomarkers (e.g., polygenic risk scores), offer promise for improved early detection and risk stratification. Additionally, newer therapeutic strategies targeting inflammation and insulin resistance are being explored to mitigate cardiovascular risks in this population. …”
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Research on Fabric Defect Detection Algorithm Based on Lightweight YOLOv7-Tiny by Tang Li, Mei Shunqi, Shi Yishan, Zhou Shi, Zheng Quan, Hongkai Jiang, Xu Qiao, Zhang Zhiming

“…The current advanced neural network models are expanding in size and complexity to achieve improved detection accuracy. This study designs a lightweight fabric defect detection algorithm based on YOLOv7-tiny, called YOLOv7-tiny-MGCK. …”
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Complementary Local–Global Optimization for Few-Shot Object Detection in Remote Sensing by Yutong Zhang, Xin Lyu, Xin Li, Siqi Zhou, Yiwei Fang, Chenlong Ding, Shengkai Gao, Jiale Chen

“…Few-shot object detection (FSOD) in remote sensing remains challenging due to the scarcity of annotated samples and the complex background environments in aerial images. …”
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